The CpxR regulates type VI secretion system 2 expression and facilitates the interbacterial competition activity and virulence of avian pathogenic Escherichia coli.

Systemic infections caused by avian pathogenic Escherichia coli (APEC) are economically devastating to poultry industries worldwide and are also potentially threatening to human health. Pathogens must be able to precisely modulate gene expression to facilitate their survival and the successful infection. The Cpx two-component signal transduction system (TCS) regulates surface structure assembly and virulence factors implicated in Gram-negative bacterial pathogenesis. However, the roles of the Cpx TCS in bacterial fitness and pathogenesis during APEC infection are not completely understood. Here, we show that the Cpx TCS response regulator CpxR is critical to the survival and virulence of APEC. Inactivation of cpxR leads to significant defects in the interbacterial competition activity, invasion and survival of APEC in vitro and in vivo. Moreover, activation of CpxR positive regulates the expression of the APEC type VI secretion system 2 (T6SS2). Further investigations revealed that phosphorylated CpxR directly bound to the T6SS2 hcp2B promoter region. Taken together, our results demonstrated that CpxR contributes to the pathogensis of APEC at least through directly regulating the expression and function of T6SS2. This study broadens understanding of the regulatory effect of Cpx TCS, thus elucidating the mechanisms through which Cpx TCS involved in bacterial virulence.

The synthesis and adsorption-dispersion properties of PPEGMA-PVPA copolymers in cement paste.

This study reports the synthesis of a novel superplasticizer, poly(poly(ethylene glycol)methacrylate)-poly(vinylphosphonic acid) (PPEGMA-PVPA), containing phosphate moieties via solution radical polymerization. By adjusting the feed ratios of monomers, PPEGMA-PVPA copolymers with different phosphate group densities were obtained, and their chemical structure was characterized via FT-IR, 1H NMR spectroscopy and ICP-OES. The results demonstrated that about 70% of the VPA monomer was polymerized. The thermostability of PPEGMA-PVPA was also determined through DSC and TGA. The adsorption-dispersion performance onto cement pastes was investigated using mini-slump test, TOC and zeta potential analysis. It was demonstrated that the adsorption capacity of PPEGMA-PVPA onto cement paste was about 1.4 times stronger than that of the reference polycarboxylate superplasticizer and exhibited excellent adsorption-dispersion performance.

Predictive value of glycoprotein DKK3 for early neurological deterioration after ischemic stroke.

OBJECTIVE: To explore the value of serum Dickkopf-3 (sDKK3) in predicting Early Neurological Deterioration (END) and in-hospital adverse outcomes in acute ischemic stroke (AIS) patients. METHODS: AIS patients (n = 200) were included and assessed by the National Institutes of Health Stroke Rating Scale. Serum Dkk3 levels were assessed by ELISA. END was defined as an increase of ≥ 4 points in NIHSS score within 72h. The biological threshold of sDKK3 level and END occurrence were predicted based on X-tile software. Primary outcomes were END and all-cause death, and the secondary outcome was ICU admission during hospitalization. The logistic regression model and Cox risk regression model were applied to evaluate the relationship between DKK3 level and END incidence, all-cause in-hospital mortality, and in-hospital adverse outcomes (ICU admission). RESULTS: During hospitalization, the incidence of END in patients with AIS was 13.0 %, and the mortality rate within 7 days after END was 11.54 % (3/26). In patients below the serum DKK3 cutoff (93.0 pg/mL), the incidence of END was 43.5 % (20/48). Patients with lower sDKK3 levels were associated with a 1.188-fold increased risk of developing END (OR = 1.188, 95 % CI 1.055‒1.369, p < 0.0001). However, there was no significant association with admission to the ICU. sDKK3 below the threshold (93.0 pg/mL) was a risk factor for death. CONCLUSION: Predictive threshold levels of serum DKK3 based on X-tile software may be a potential predictive biomarker of in-hospital END in patients with AIS, and low levels of DKK3 are independently associated with increased in-hospital mortality.

Screening of Key Genes Associated with Ischemic Stroke via Microarray Data.

OBJECTIVE: To promote understandings about the pathogenesis of ischemic stroke (IS) through mining key genes, functions and pathways with microarray technology. METHODS: Differentially expressed genes (DEGs) in blood between patients with IS and healthy people were screened out through comparing microarray data obtained from Gene Expression Omnibus. Overrepresented functions in DEGs were revealed by Gene Ontology (GO) enrichment analysis. Interaction network was constructed for the top 24 DEGs with information from Human Protein Reference Database (HPRD). Relevant microRNAs (miRNAs) were retrieved from three databases: TargetScan, miRBase and miRanda. RESULTS: A total of 503 DEGs were obtained. Functional enrichment analysis showed that immune response, signaling pathways and apoptosis were significantly over-represented. Six key genes with big degree, betweenness and clustering coefficient were then revealed, which might play important roles in the development of IS. In addition, 57 differentially expressed miRNAs targeting the 6 genes were retrieved. CONCLUSIONS: Our study provides insights into the pathogenesis of IS and potential targets to treat the disease.Dépistage de gènes clés associés à l'accident vasculaire cérébral ischémique au moyen de données obtenues par la technique des biopuces.

IASA: An IoU-aware tracker with adaptive sample assignment.

Most of existing trackers develop tracking in a tracking head network, which is composed of classification branch and regression branch. However, they lack a meaningful exploration of how to define positive and negative samples during training, which can significantly affect tracking performance. Furthermore, they cannot provide a reliable ranking by using classification scores or a combination of classification and regression scores to obtain candidate locations. To address these issues, we propose an intersection over union (IoU) aware tracker with adaptive sample assignment (IASA). The IASA introduces an IoU-aware classification score to achieve a more accurate ranking for candidate tracking locations. We also propose a new loss function, IoU-focal loss, to train the anchor-free tracker IASA to predict the classification scores and introduce a star-shaped box feature representation to refine classification features. To explore the actual content of the training samples, we develop an adaptive sample assignment (ASA) strategy to divide the positive and negative samples according to the statistical characteristics of the sample IoUs. By combining these two proposed components, the IASA tracker treats the tracking task as a classification and a regression problem. It directly finds the candidate tracking location in the classification branch and then regresses the four distances from the location to the four sides of the tracking box. Experimental results show that the proposed IASA can achieve state-of-the-art performance on seven public datasets.

Effects of thiram exposure on liver metabolism of chickens.

Pesticides are widely used to control crop diseases, which have made an important contribution to the increase of global crop production. However, a considerable part of pesticides may remain in plants, posing a huge threat to animal safety. Thiram is a common pesticide and has been proven that its residues in the feed can affect the growth performance, bone formation, and intestinal health of chickens. However, there are few studies on the liver metabolism of chickens exposed to thiram. Here, the present study was conducted to investigate the effect of thiram exposure on liver metabolism of chickens. Metabolomics analysis shows that 62 metabolites were down-regulated (ginsenoside F5, arbekacin, coproporphyrinogen III, 3-keto Fusidic acid, marmesin, isofumonisin B1, 3-Hydroxyquinine, melleolide B, naphazoline, marmesin, dibenzyl ether, etc.) and 35 metabolites were up-regulated (tetrabromodiphenyl ethers, deoxycholic acid glycine conjugate, L-Palmitoylcarnitine, austalide K, hericene B, pentadecanoylcarnitine, glyceryl palmitostearate, quinestrol, 7-Ketocholesterol, tetrabromodiphenyl ethers, etc.) in thiram-induced chickens, mainly involved in the metabolic pathways including glycosylphosphatidylinositol (GPI)-anchor biosynthesis, porphyrin and chlorophyll metabolism, glycerophospholipid metabolism, primary bile acid biosynthesis and steroid hormone biosynthesis. Taken together, this research showed that thiram exposure significantly altered hepatic metabolism in chickens. Moreover, this study also provided a basis for regulating the use and disposal of thiram to ensure environmental quality and poultry health.

Investigation of the Effect of Particle Surface Charge and Dispersion Stability on Latex Behavior in Cement Using Non-Ionic and Traditional Latexes.

In this work, a novel total non-ionic polystyrene-polyurethane (PS-PU) composite latex was synthesized with polymerizable polyethylene glycol ether. Contrary to traditional styrene-butyl acrylate latex (St-BA), PS-PU has a smaller size and superior dispersion stability, and it is stable in saturated Ca(OH)2 even after 72 h. In fresh-mixed mortars, PS-PU showed a little adverse effect on workability and insignificant air entrainment, with little defoamer consumption. The retardation effect of PS-PU is also much milder than traditional St-BA. As for strength, PS-PU showed a less adverse effect on early and late age compressive strength, but its effect on flexural strength is not as pronounced as St-BA at high dosages (4% and 6%). The different behavior in cementitious materials between PS-PU and St-BA can be reasoned from their different adsorption behavior and surface charge properties, as the results from characterizations suggest. The non-ionic nature of PS-PU made it less prone to destabilization and adsorption, which turned out as the aforementioned behavior in cementitious systems. The difference can further be ascribed to the difference in their polymeric structure and properties.

Learning to Synthesize Compatible Fashion Items Using Semantic Alignment and Collocation Classification: An Outfit Generation Framework.

The field of fashion compatibility learning has attracted great attention from both the academic and industrial communities in recent years. Many studies have been carried out for fashion compatibility prediction, collocated outfit recommendation, artificial intelligence (AI)-enabled compatible fashion design, and related topics. In particular, AI-enabled compatible fashion design can be used to synthesize compatible fashion items or outfits to improve the design experience for designers or the efficacy of recommendations for customers. However, previous generative models for collocated fashion synthesis have generally focused on the image-to-image translation between fashion items of upper and lower clothing. In this article, we propose a novel outfit generation framework, i.e., OutfitGAN, with the aim of synthesizing a set of complementary items to compose an entire outfit, given one extant fashion item and reference masks of target synthesized items. OutfitGAN includes a semantic alignment module (SAM), which is responsible for characterizing the mapping correspondence between the existing fashion items and the synthesized ones, to improve the quality of the synthesized images, and a collocation classification module (CCM), which is used to improve the compatibility of a synthesized outfit. To evaluate the performance of our proposed models, we built a large-scale dataset consisting of 20 000 fashion outfits. Extensive experimental results on this dataset show that our OutfitGAN can synthesize photo-realistic outfits and outperform the state-of-the-art methods in terms of similarity, authenticity, and compatibility measurements.

Tuning the Hydration Acceleration Efficiency of Calcium Carbonate by Pre-Seeding with Calcium Silicate Hydrate.

Nanomaterials are promising candidates for refined performance optimization of cementitious materials. In recent years, numerous studies about the performance improvement of nanomaterials using polymers have been conducted, but the modification of cement-oriented nanomaterials with inorganic modifiers is seldom assessed. In this study, we explored the performance tuning and optimization of nanomaterials by inorganic modification. In this work, hydration acceleration efficiency of calcium carbonate (CaCO3, CC) was tuned via surface deposition with calcium silicate hydrate (C-S-H) nanogel through seeding. Multiple calcium carbonate-calcium silicate hydrate (CC-CSH) samples with varying degrees of surface modification were prepared via dosage control. According to characterizations, the degree of C-S-H modification on the CaCO3 surface has a maximum that is controlled by available surface space. Once the available space is depleted, excessive C-S-H turns into free form and causes adhesion between CC-CSH particles. The resultant CC-CSH samples in this work showed enhanced hydration acceleration efficiency that is tuned by the actual degree of C-S-H modification. Elevated C-S-H modification causes CC-CSH's acceleration behavior to shift to enhanced early-age acceleration. According to mortar strength tests, CC-CSH with 5% C-S-H modification showed the most balanced performance, while CC-CSH with higher C-S-H modification showed faster early-age strength development at the cost of lower later-age strength. The inferior later-age strength of highly C-S-H-modified CC-CSH samples may be due to the coarsening of hydration products and stiffening of their network, as well as agglomeration caused by C-S-H adhesion. This study may offer a novel route for performance tuning of cement-oriented nanomaterials.

Advances in Organic Rheology-Modifiers (Chemical Admixtures) and Their Effects on the Rheological Properties of Cement-Based Materials.

Organic rheology modifiers, especially superplasticizers and viscosity-modifying admixtures (VMAs), have become key components for the workability optimization of modern concrete. The development of these admixtures is crucial to the further performance improvement of modern concrete under different casting and service conditions. Many of the former reviews have summarized research advances in respect of these admixtures from chemical and material perspectives, focusing on the effects of structure and the performance. In this paper, from a rheological perspective, an overview is provided of the microscale behavior of polycarboxylate (PCE) superplasticizers and VMAs (e.g., adsorption, conformation, and bridging) in terms of the evolution of the microstructure of the paste, the effect of chemical structure on the yield stress, the apparent viscosity and thixotropy of cement-based materials, and the structure design of these admixtures. Most importantly, in addition to a general discussion with assumptions (monolayer adsorption of a "flat" conformation, with each molecule on a single particle; statistical polymer composition), special conditions (e.g., preferential adsorption, depletion effects, hydration modification effects, and the polydispersity of the polymer composition) are discussed. Newly developed admixtures, realized through regulation of the microscale behavior, and by the modification of adsorption, topological structure, and molecular frame, are introduced.

TGAN: A simple model update strategy for visual tracking via template-guidance attention network.

Visual attention has been widely used in various fields of visual tasks in recent years. Recently, visual trackers based on probabilistic discriminative model prediction (PrDiMP) and Siamese box adaptive network (SiamBAN) have attracted much attention due to their excellent performance and high efficiency. However, the target template of the model in both the PrDiMP and SiamBAN is not updated online, and feature vectors of the template image and the search image are independent of each other in the IoU-Net and Siamese frameworks. In this research, we proposed a template-guidance attention network in both the IoU-Net (denoted as TGAN-I) and Siamese (denoted as TGAN-S) frameworks for visual tracking. TGAN-I and TGAN-S can comprehensively utilize the feature information of the template image and search image, and provide an implicit way to update the template. By utilizing a simple template update strategy, the TGAN-I and TGAN-S trackers can be more robust under certain challenging conditions such as occlusion and deformation. Besides, we introduce a channel and spatial attention module in feature maps of the template image and search image for adaptive feature refinement. Deformable convolutional networks are further used to enhance the model generalization capability in various transformations aspect ratios and scales of tracking targets. To verify the effectiveness of the proposed method, we evaluate the TGAN-I and TGAN-S trackers on six benchmarks and achieve state-of-the-art results. In particular, the TGAN-I method outperforms the strong baseline, PrDiMP, by 0.323 → 0.355 and 0.471 → 0.501 of EAO score on VOT2019 and VOT2016, respectively.

Predictive value of glycoprotein DKK3 for early neurological deterioration after ischemic stroke

Abstract Objective To explore the value of serum Dickkopf-3 (sDKK3) in predicting Early Neurological Deterioration (END) and in-hospital adverse outcomes in acute ischemic stroke (AIS) patients. Methods AIS patients (n = 200) were included and assessed by the National Institutes of Health Stroke Rating Scale. Serum Dkk3 levels were assessed by ELISA. END was defined as an increase of ≥ 4 points in NIHSS score within 72h. The biological threshold of sDKK3 level and END occurrence were predicted based on X-tile software. Primary outcomes were END and all-cause death, and the secondary outcome was ICU admission during hospitalization. The logistic regression model and Cox risk regression model were applied to evaluate the relationship between DKK3 level and END incidence, all-cause in-hospital mortality, and in-hospital adverse outcomes (ICU admission). Results During hospitalization, the incidence of END in patients with AIS was 13.0 %, and the mortality rate within 7 days after END was 11.54 % (3/26). In patients below the serum DKK3 cutoff (93.0 pg/mL), the incidence of END was 43.5 % (20/48). Patients with lower sDKK3 levels were associated with a 1.188-fold increased risk of developing END (OR = 1.188, 95 % CI 1.055‒1.369, p < 0.0001). However, there was no significant association with admission to the ICU. sDKK3 below the threshold (93.0 pg/mL) was a risk factor for death. Conclusion Predictive threshold levels of serum DKK3 based on X-tile software may be a potential predictive biomarker of in-hospital END in patients with AIS, and low levels of DKK3 are independently associated with increased in-hospital mortality.

Erratum to "Magnetic Resonance Imaging of Atherosclerosis Using CD81-Targeted Microparticles of Iron Oxide in Mice".

[This corrects the article DOI: 10.1155/2015/758616.].

Template-Free Synthesis of Hollow/Porous Organosilica-Fe3O4 Hybrid Nanocapsules toward Magnetic Resonance Imaging-Guided High-Intensity Focused Ultrasound Therapy.

Entirely differing from the common templating-based multistep strategy for fabricating multifunctional hollow mesoporous silica nanoparticles (HMSN), a facile and template-free synthetic strategy has been established to construct a unique hollow/mesoporous organosilica nanocapsule (OSNC) concurrently encapsulating both isopentyl acetate (PeA) liquid and superparamagnetic iron oxides inside (denoted as PeA@OSNC). This novel material exhibits ultrasmall and uniform particle size (∼82 nm), high surface area (∼534 m2·g-1), and excellent colloidal stability in aqueous solution. The oil-phase PeA with relatively low boiling point (142 °C) and high volatility not only plays a crucial role in formation of a large hollow cavity from the viewpoint of structural design but also enables the PeA@OSNC to act as an efficient enhancement agent in high-intensity focused ultrasound (HIFU) therapy. Moreover, the unique satellite-like distribution of Fe3O4 nanoparticles (NP) on the organosilica shell offered excellent magnetic resonance imaging (MRI) contrast capability of PeA@OSNC in vitro and in vivo. More importantly, such a novel theranostic agent has favorable biosafety, which is very promising for future clinical application in MRI-guided HIFU therapy.

Magnetic Resonance Imaging of Atherosclerosis Using CD81-Targeted Microparticles of Iron Oxide in Mice.

The goal of this study is to investigate the feasibility of using CD81- (Cluster of Differentiation 81 protein-) targeted microparticles of iron oxide (CD81-MPIO) for magnetic resonance imaging (MRI) of the murine atherosclerosis. CD81-MPIO and IgG- (Immunoglobulin G-) MPIO were prepared by covalently conjugating, respectively, with anti-CD81 monoclonal and IgG antibodies to the surface of the tosyl activated MPIO. The relevant binding capability of the MPIO was examined by incubating them with murine bEnd.3 cells stimulated with phenazine methosulfate (PMS) and its effect in shortening T2 relaxation time was also examined. MRI in apolipoprotein E-deficient mice was studied in vivo. Our results show that CD81-MPIO, but not IgG-MPIO, can bind to the PMS-stimulated bEnd.3 cells. The T2 relaxation time was significantly shortened for stimulated bEnd.3 cells when compared with IgG-MPIO. In vivo MRI in apolipoprotein E-deficient mice showed highly conspicuous areas of low signal after CD81-MPIO injection. Quantitative analysis of the area of CD81-MPIO contrast effects showed 8.96- and 6.98-fold increase in comparison with IgG-MPIO or plain MPIO, respectively (P < 0.01). Histological assay confirmed the expression of CD81 and CD81-MPIO binding onto atherosclerotic lesions. In conclusion, CD81-MPIO allows molecular assessment of murine atherosclerotic lesions by magnetic resonance imaging.